---
base_model: cardiffnlp/twitter-roberta-base-sentiment-latest
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: twitter-roberta-base-sentiment-latest
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# twitter-roberta-base-sentiment-latest

This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment-latest](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment-latest) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3302
- Accuracy: 0.784

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 600
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8113        | 0.12  | 30   | 0.7971          | 0.418    |
| 0.6733        | 0.24  | 60   | 0.6551          | 0.469    |
| 0.5712        | 0.36  | 90   | 0.5713          | 0.522    |
| 0.5234        | 0.48  | 120  | 0.5311          | 0.565    |
| 0.5406        | 0.6   | 150  | 0.4938          | 0.6595   |
| 0.4856        | 0.72  | 180  | 0.4482          | 0.692    |
| 0.4732        | 0.84  | 210  | 0.4147          | 0.7185   |
| 0.4217        | 0.96  | 240  | 0.4038          | 0.726    |
| 0.4097        | 1.08  | 270  | 0.3828          | 0.7375   |
| 0.3911        | 1.2   | 300  | 0.3928          | 0.735    |
| 0.3779        | 1.32  | 330  | 0.3767          | 0.7555   |
| 0.3829        | 1.44  | 360  | 0.3705          | 0.74     |
| 0.3596        | 1.56  | 390  | 0.3905          | 0.744    |
| 0.3626        | 1.68  | 420  | 0.3712          | 0.7425   |
| 0.3763        | 1.8   | 450  | 0.3679          | 0.752    |
| 0.3722        | 1.92  | 480  | 0.3353          | 0.7805   |
| 0.3387        | 2.04  | 510  | 0.3504          | 0.768    |
| 0.3247        | 2.16  | 540  | 0.3573          | 0.766    |
| 0.3242        | 2.28  | 570  | 0.3526          | 0.7775   |
| 0.4003        | 2.4   | 600  | 0.3413          | 0.7785   |
| 0.352         | 2.52  | 630  | 0.3547          | 0.763    |
| 0.3521        | 2.64  | 660  | 0.3449          | 0.7835   |
| 0.29          | 2.76  | 690  | 0.3270          | 0.7875   |
| 0.3017        | 2.88  | 720  | 0.3302          | 0.784    |
| 0.3086        | 3.0   | 750  | 0.3401          | 0.782    |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1